What does AI say about your G25 results?

Modern population averages (top distances): French_Brittany: 0.02110
Welsh: 0.02232
English_Cornwall: 0.02364
English: 0.02389
Dutch: 0.02541
Scottish: 0.02573
French_Pas-de-Calais: 0.02574
Irish: 0.02636

(German, Danish, Norwegian all >0.032)
Closest ancient samples:

France_Hauts-de-France_Aisne_LaTene_IA (Continental Celtic): 0.02217

Multiple Belgium_Flanders medieval samples (Celto-Germanic zone)

Several England Iron Age / Late Iron Age / Roman / Black Death medieval samples (mostly pre- or early Anglo-Saxon British)

Early medieval Saxon/Germanic samples appear farther down (~0.0246+)

Summary:
These coordinates place the sample firmly on the Northwest European cline, with a clear Celtic shift. The strongest modern pulls are toward Breton, Welsh, and Cornish averages, while general English remains very close. Continental Germanic populations (Dutch, German, Danish) are noticeably more distant.Ancient distances support this pattern: the top hits are a northern French La Tène Celtic sample and multiple English Iron Age / Roman-era samples, which largely represent the pre-Anglo-Saxon Brittonic population. Early medieval Saxon-like samples rank lower.Overall, the profile appears more Celtic-shifted than the average modern English person, suggesting a stronger Insular/Continental Celtic (Brythonic/Gaulish-like) substrate with only a moderate Germanic (Anglo-Saxon and later) layer. This is typical for ancestry from western/southwestern England, Wales, or regions with Breton/French Celtic influence.Suggestions for further analysis: Celtic vs Germanic nMonte models using England_IA / France_IA (Celtic) versus England_EMA_Saxon / Danish_VA (Germanic) proxies.

Google AI

Based on your G25 scaled coordinates, your profile most closely aligns with populations from Northern and Western Europe, particularly in the North Sea region. Your closest individual matches are likely to be Northern German, Dutch, English, or Danish.

Below is an estimate of your ethnic breakdown as it might appear on a Vahaduo Admixture "Single" tab. Please note that this is a simulated model based on common modern reference averages; for a precise result, you should paste your coordinates into the Vahaduo TARGET tab and use a full reference datasheet (like G25 Modern Averages) in the SOURCE tab.

Estimated Ethnicity Breakdown (Single Tab)
Population Percentage
German_North 32.4%
English 24.8%
Dutch 21.2%
Danish 12.6%
Irish 9.0%

Distance: 0.021008 (Lower distance indicates a better fit; values under 0.02 are considered excellent).
Genetic Observations:
Northern European Core: Your coordinates show high values in the first few dimensions (0.132, 0.126), which is characteristic of Northwest European populations.
North Sea Affinity: The strong pull towards Northern Germany and the Netherlands suggests a genetic profile that sits at the crossroads of Germanic and Insular Celtic (British/Irish) clusters.
Fit Quality: A distance of approximately 0.021 is a very respectable match, meaning your coordinates are well-represented by these standard modern averages.



ChatGPT

Best Fit Populations (Approximate)

If I had to place this individual on a PCA map, they would likely fall closest to:

South Scandinavian (Danish / South Swedish)
North German
English (especially East Anglia / Southeast England)
Dutch
Estimated Ethnicity Breakdown (Scaled Approximation)

This is a rough G25-style estimate, not exact:

Region Approx %
English 40–50%
Scandinavian (Danish/Swedish/Norwegian) 25–35%
German / Dutch 15–25%
Celtic (Irish/Scottish/Welsh) 5–10%
Summary

Overall, this person is most likely:

Northwest European with a strong North Sea / Scandinavian component
(Something like English + Scandinavian + North German/Dutch)

If I had to guess a single modern ethnicity:

Danish–English mixed or North German + English would be very plausible.

Quote:

---

Originally Posted by Gannicus

Modern population averages (top distances): French_Brittany: 0.02110
Welsh: 0.02232
English_Cornwall: 0.02364
English: 0.02389
Dutch: 0.02541
Scottish: 0.02573
French_Pas-de-Calais: 0.02574
Irish: 0.02636

(German, Danish, Norwegian all >0.032)
Closest ancient samples:

France_Hauts-de-France_Aisne_LaTene_IA (Continental Celtic): 0.02217

Multiple Belgium_Flanders medieval samples (Celto-Germanic zone)

Several England Iron Age / Late Iron Age / Roman / Black Death medieval samples (mostly pre- or early Anglo-Saxon British)

Early medieval Saxon/Germanic samples appear farther down (~0.0246+)

Summary:
These coordinates place the sample firmly on the Northwest European cline, with a clear Celtic shift. The strongest modern pulls are toward Breton, Welsh, and Cornish averages, while general English remains very close. Continental Germanic populations (Dutch, German, Danish) are noticeably more distant.Ancient distances support this pattern: the top hits are a northern French La Tène Celtic sample and multiple English Iron Age / Roman-era samples, which largely represent the pre-Anglo-Saxon Brittonic population. Early medieval Saxon-like samples rank lower.Overall, the profile appears more Celtic-shifted than the average modern English person, suggesting a stronger Insular/Continental Celtic (Brythonic/Gaulish-like) substrate with only a moderate Germanic (Anglo-Saxon and later) layer. This is typical for ancestry from western/southwestern England, Wales, or regions with Breton/French Celtic influence.Suggestions for further analysis: Celtic vs Germanic nMonte models using England_IA / France_IA (Celtic) versus England_EMA_Saxon / Danish_VA (Germanic) proxies.

---

I'll add that qpAdm is a mixed bag. Sometimes it puts me at majority IA Germanic and sometimes majority Celtic IA.


Attachment 147534


At the same time depending on outgroups, I can be modeled as 100% British IA, 100% Continental Celtic IA or Germanic IA.

Interpretation:

This is a solid two-way qpAdm model with an excellent p-value, indicating that the sample can be reasonably modeled as a mixture of these two Iron Age sources.France_Yonne_IA.SG represents Continental Celtic / northern Gaulish Iron Age ancestry (Yonne is in north-central France; this proxy captures pre-Roman La Tène / Celtic Gaulish-related populations in the broader northern French zone).
Norway_IA.SG represents Iron Age Scandinavian / early Germanic-related ancestry from Norway (pre-Viking Nordic Iron Age profile).

The roughly 47% / 53% split shows a balanced contribution from a Celtic (Continental Gaulish-like) source and a Germanic / North Germanic (Scandinavian Iron Age) source.Caveats / Context:Both proxies are Iron Age Northwest European populations and are genetically relatively close to each other. qpAdm can sometimes struggle to sharply distinguish subtle differences between northern Gaulish Celts and early Scandinavian groups, as they share much of the same underlying Steppe + EEF + WHG layers.

This model treats "Celtic" broadly via the French IA proxy and "Germanic" via the Norwegian IA proxy. In reality, many modern English, Dutch, and northwest French profiles show similar mixed signals due to historical overlap (e.g., Belgae, Anglo-Saxon migrations, etc.).
The near-even split aligns with your previous G25 results: a clear Celtic shift (strong pulls to Breton, Welsh, Cornish, and French La Tène) combined with enough Germanic / North Sea affinity to keep general English and FST to English.HO extremely close.

Overall picture from all runs combined:

Your coordinates reflect a Northwest European profile with substantial Insular/Continental Celtic (Brythonic/Gaulish-like) ancestry layered with a comparable Germanic (Anglo-Saxon / early Scandinavian-like) component. This is very typical for many people of English ancestry (especially western or southern England), as well as some Breton or northwest French individuals.Would be interesting to test more refined models (e.g., adding England_IA as a third source, or using England_EMA_Saxon + France_IA, or Denmark_IA instead of Norway_IA) to see if the proportions shift.

,0.140002,0.136081,0.064865,0.050711,0.040931,0.01 3108,-0.001175,0.003461,0.006545,0.009112,-0.002111,0.008243,-0.011893,-0.013074,0.02253,0.007027,-0.008475,0.004687,0.002011,-0.003502,0.002371,0.005441,-0.005669,0.012773,0.005868. Do my g25 coordinates lean more Celtic or Germanic?

ChatGPT says:

Short answer: your coordinates lean more toward Northwestern/Celtic-shifted European than strongly Germanic, but they’re in the overlap zone—not purely one or the other.
How to read your numbers (in plain terms)
G25 coordinates are basically plotting you in a genetic map of Europe. The key signals in yours:
Positive first values (0.14 / 0.136) → firmly Northwestern European
Moderate third component (0.064) → typical of Atlantic-facing populations
Low/near-zero later components → not much Southern/Eastern pull
Celtic vs Germanic (genetically speaking)
This distinction is subtle genetically—these groups are very close. But broadly:
Celtic-shifted populations (Irish, Welsh, Scottish):
Slightly more “Atlantic” pull
A bit more drift away from continental Europe
Germanic-shifted populations (English, Dutch, German):
Slightly more “North Sea / continental” pull
Closer to mainland Europe genetically
Your profile suggests:
You sit comfortably in the British Isles cluster
You show:
A noticeable Atlantic/Celtic tilt
But also clear overlap with English/North Sea Germanic profiles
�� So the best description:
British Isles type, slightly Celtic-leaning but still within typical English/Germanic overlap
What you are not showing strongly:
Not strongly Scandinavian (would shift differently)
Not Southern European
Not Eastern European

Your most realistic ratio is:

Nordic: ~60–65%
Celtic: ~35–40%

Nothing, because Gemini is currently unable to perform a correct simple analysis of G25 coordinates.

Quote:

---

Originally Posted by Flashball

Nothing, because Gemini is currently unable to perform a correct simple analysis of G25 coordinates.

---

Have you tried using any other AIs?

I tried it and surprisingly it was not very good. It missed all my Eastern European and did not even identify my specific NW European ethnicities in correct proportions. It did not match the main G25 calculator results or Illus either oddly. May try another AI too.

Oh, this thread made me debate against Artificial Intelligences haha xD

My original question:

Quote:

---

Without considering my current location and my interaction history in your memory, but only the data from the archive with modern populations and my G25 coordinates, can you guess my ethnic composition and recent ancestry? It doesn't have to be very precise, if there are very close populations, you can give a broad or regional result, or even synthetic. Consider giving a result considering up to a maximum of three populations or three groups; and also a more comprehensive one of up to a maximum of five populations or five mixed groups or five regions. My coordinates: Fabricius_K13-G25,0.062759,0.144232,0.046361,0.008926,0.037920,0 .003151,-0.005473,0.001473,0.011898,0.019353,0.002219,0.001 776,-0.002418,-0.003636,0.003109,-0.000951,-0.001291,-0.001565,-0.003132,0.000172,0.000346,-0.001020,0.000361,-0.001119,-0.000207

---

In short: for AIs, my Northeast European scores (Lithuanians, Poles, etc.) are proxies for the calculator to adapt to my Iberian + African + the supposed Amerindian component. To me it sounds absurd, since typically I score >12% Lithuanian.

Although it sounds arrogant, I believe that I refuted Grok and ChatGPT's arguments with data. I believe that these intelligences were directed more towards maintaining the position than towards the truth (although ChatGPT admitted a little that I am not a typical Iberian.

Not good. At least not for me. He probably considers only individual distances (which many here prefer, but which for mestizos does not work) and does not try to create an adaptation model like the calculators made for this. The AIs can perceive an Amerindian that in the calculators, when they appear, does not exceed 0.4% and does not detect the Baltic. He notes the SSA, which most likely, like the supposed Amerindian, must be much older than a "great-great-grandfather" (~6%) but fragmented into more colonial ways.

Those who remember me from the episode of the update to v2.5 of MyHeritage know that I get very angry when they deny my ancestry from Northeast Europe. But I invite anyone who wants to comment on the conclusion of the AIs. I will respect every opinion on this. The truth is more important than the wish.

Grok:
https://grok.com/share/bGVnYWN5LWNvc...a-77ac7a29242f

Conclusion of Grok:

Quote:

---

Simple explanation of the difference
• Canarian + Berber synthetic: Already a near-ideal blend of Iberian + Northwest African. Little residual distance left → models stay clean with Berber/Moroccan/Tunisian + Spanish_Canarias sources. No need for Central European “helpers.”
• Your real sample: Slightly different balance or tiny extra drift in some PCs. The overfit models “borrow” Central European averages (Sorb, Polish, German, Slovenian, Belgian) because they happen to reduce the mathematical error in those dimensions. These are fitting artifacts, not recent ancestry from Poland, Lithuania, or Germany.

---

ChatGPT:
https://chatgpt.com/share/69c80701-1...d-2fe563c6d566

Conclusion of GPT:

Quote:

---

✅ Final interpretation (refined)
Predominantly Iberian (~70–80%)
with
moderate West African (~15–25%)
trace Amerindian (~<1%)
But the Iberian itself is:
Not perfectly “Atlantic Iberian” — slightly shifted toward Central/Mediterranean Europe

�� In plain language
If we translate everything you did:
You are essentially Iberian, but your European side is not from a very tight, isolated Iberian genetic pocket — it carries a faint but real broader European influence.

---

I used the samples below to argue against the AIs:

Spoiler!

Surui,0.057822,-0.317454,0.117134,0.10672,-0.113806,-0.015395,-0.325819,-0.391691,-0.017548,-0.020775,0.002079,-0.004676,0.002319,0.035864,-0.013491,0.000583,0.0109,-0.001242,0.000251,0.001276,-0.003544,0.012662,-0.006779,-0.007447,-0.009149
Spanish_Canarias,0.081294,0.145702,0.030269,-0.012903,0.037837,-0.006224,-0.006494,0.000814,0.031604,0.029052,-0.000496,0.005261,-0.007175,-0.013617,0.011022,-0.002198,-0.002738,-0.003487,-0.010843,0.000987,0.000604,-0.00643,0.001641,-0.003418,0.001702
Yoruba,-0.630062,0.062501,0.022113,0.016708,0.000503,0.012 474,-0.044417,0.047767,-0.048881,0.032769,0.004621,0.00079,0.023056,0.0009 51,0.012523,-0.009607,0.007076,0.000449,0.006022,-0.00299,0.001554,0.002316,-0.001759,-0.000471,-0.000425
Iberian,0.110402,0.1415784,0.0398687,-0.0005169,0.0431142,-0.0018739,-0.001906,0.0019369,0.0234939,0.0314933,-0.0027015,0.0076052,-0.0145158,-0.0125172,0.0098462,0.0006419,-0.0024884,-0.0003313,-0.0028162,-0.0015244,0.0034283,-0.0009043,-0.0022295,-0.0032113,0.0005154
Canarians+SouthAmerindian,0.069558,-0.085876,0.0737015,0.0469085,-0.0379845,-0.0108095,-0.1661565,-0.1954385,0.007028,0.0041385,0.0007915,0.0002925,-0.002428,0.0111235,-0.0012345,-0.0008075,0.004081,-0.0023645,-0.005296,0.0011315,-0.00147,0.003116,-0.002569,-0.0054325,-0.0037235
Canarian&Amerindian+SSA,-0.280252,-0.0116875,0.0479072,0.0318082,-0.0187408,0.0008322,-0.1052868,-0.0738358,-0.0209265,0.0184538,0.0027062,0.0005412,0.010314,0 .0060372,0.0056442,-0.0052072,0.0055785,-0.0009578,0.000363,-0.0009292,0.000042,0.002716,-0.002164,-0.0029518,-0.0020742
Iberian_99%+Amerindian1%,0.10986709571,0.136957894 6,0.040640703,0.0005578676000000001,0.0415307551,-0.00204042671,-0.00518481,-0.0020383476000000005,0.02309504957,0.03097634414,-0.002651983571,0.007484402286,-0.014364694857100001,-0.01202024943,0.009609107999999998,0.000653475286,-0.0023525031399999996,-0.0003290727143,-0.0027896537143000002,-0.001491827429,0.003356762714,-0.0007539398599999999,-0.0022837935710000004,-0.003260951286,0.0004122217139999999
Iberian&Amerindian(99+1)94%+SSA6%,0.1024664197529, 0.13621455732399998,0.0404593118,0.000720248924,0. 041119037548999995,-0.0018924291128999998,-0.0055806569,-0.0015381757940000004,0.0223718774043,0.0310020473 686,-0.00257972540229,0.00741967576314,-0.013981454578529002,-0.011893853602399999,0.00964059275,0.0005484930331 4,-0.0022532472755999993,-0.000313536154157,-0.0026899005101570003,-0.00150827748771,0.0033423292538599996,-0.0007153846283999999,-0.0022701998019900005,-0.00323386510644,0.0004044061635599999
Canarian+Berber,0.008159682000000001,0.14055894,0. 0134109275,-0.04245722,0.031913327500000005,-0.0196339884,-0.01637574945,0.005806182105,0.0468999305,0.029629 9915,0.00305075158,-0.0006072873500000001,0.00745038525,-0.015203796999999998,0.0137723865,-0.009233038950000001,-0.00270557895,-0.0127975379,-0.027406286499999998,0.00463440421,-0.007130333685,-0.021669567350000002,0.01326352525,-0.0038301179,0.0037260821

I made the ghost populations here:
https://admixr.com/ghost

Quote:

---

Originally Posted by Fabricius

...

---

Below are my results using 1003 modern official samples against coordinates of non-existent mestizo populations simulating the composition that AIs attributed to me.

Me:

Target: Fabricius_K13-G25
Distance: 0.8786% / 0.00878558
23.4
Basque_Navarre_Center
19.8
Italian_Friuli_Venezia_Giulia_Sappada
18.2
Sorb_Niederlausitz
12.0
Basque_Soule
6.6
Esan_Nigeria
5.4
BedouinB
4.4
BelgianC
3.2
Polish_Silesian
3.0
Saharawi
1.6
Sardinian
1.4
Lithuanian_PZ
0.4
Fulani
0.2
Italian_Bergamo
0.2
Kongo
0.2
Surui


Target: Fabricius_K13-G25
Distance: 1.2375% / 0.01237535 | ADC: 0.25x RC
54.8
Spanish_Canarias
23.2
German_Erlangen
9.4
Slovenian
7.4
Sorb_Niederlausitz
5.2
Esan_Nigeria


Target: Fabricius_K13-G25
Distance: 1.3616% / 0.01361609 | ADC: 0.5x RC
53.2
Spanish_Canarias
34.2
Slovenian
7.4
Afrikaner
5.2
Esan_Nigeria


Target: Fabricius_K13-G25
Distance: 3.7131% / 0.03713135 | ADC: 1x RC
71.2
Spanish_Canarias
28.8
Afrikaner



Canarian + South Amerindian


Target: Canarians+SouthAmerindian
Distance: 0.1254% / 0.00125409
44.6
Surui
12.4
Spanish_Extremadura
11.4
Basque_Navarre_Center
8.8
Spanish_Canarias
3.6
Berber_Tunisia_Chen
3.0
Karitiana
3.0
Spanish_Penedes
3.0
Tunisian_Berber_Zraoua
2.0
Basque_Soule
1.8
Quechua
1.4
Karaite_Iraq
1.4
Lithuanian_VZ
0.8
Ethiopian_Agaw
0.6
Bolivian_Pando
0.6
Italian_Friuli_Venezia_Giulia_Sappada
0.4
Bolivian_Cochabamba
0.4
Georgian_Guria
0.4
Sardinian
0.2
Mbuti
0.2
Saharawi


Target: Canarians+SouthAmerindian
Distance: 1.6808% / 0.01680808 | ADC: 0.25x RC
58.8
Bolivian_Pando
20.4
Spanish_Extremadura
16.0
Spanish_Canarias
2.8
Karaite_Iraq
2.0
Sardinian


Target: Canarians+SouthAmerindian
Distance: 1.8212% / 0.01821247 | ADC: 0.5x RC
58.6
Bolivian_Pando
40.4
Spanish_Canarias
1.0
Moroccan_Jew


Target: Canarians+SouthAmerindian
Distance: 8.4314% / 0.08431382 | ADC: 1x RC
80.6
Cree
19.4
Spanish_Canarias




Canarian & Amerindian + SSA:
Canarian&Amerindian+SSA

Target: Canarian&Amerindian+SSA
Distance: 0.0999% / 0.00099873
40.2
Yoruba
22.0
Surui
11.0
Spanish_Extremadura
6.0
Esan_Nigeria
4.6
Fulani
4.0
Basque_Soule
2.6
Basque_Biscay
2.0
Bolivian_Pando
1.6
Bolivian_Cochabamba
1.2
Tunisian_Rbaya
1.0
Mandenka
0.8
Italian_Calabria
0.6
French_Seine-Maritime
0.6
Georgian_Ajar
0.4
Sardinian
0.4
Senegal_Halpularen
0.4
Sorb_Niederlausitz
0.2
Gambian
0.2
Spanish_Catalunya_Central
0.2
Spanish_Galicia


Target: Canarian&Amerindian+SSA
Distance: 3.1491% / 0.03149130 | ADC: 0.25x RC
46.8
Fulani_Guinea
29.4
Bolivian_Pando
12.4
Iranian_Bandari_Zanji
11.4
Berber_Algeria


Target: Canarian&Amerindian+SSA
Distance: 4.5971% / 0.04597056 | ADC: 0.5x RC
64.8
Fulani_Burkina_Faso_Ziniare
30.0
Bolivian_Pando
4.4
Madagascar_Mikea
0.8
Berber_Algeria


Target: Canarian&Amerindian+SSA
Distance: 8.0270% / 0.08027032 | ADC: 1x RC
49.6
Berber_Algeria
28.2
Madagascar_Vezo
22.2
Bolivian_Pando




Iberian and Amerindian (99% Iberian average + 1% Amerindian) + SSA (Yoruba):

Target: Iberian&Amerindian(99+1)94%+SSA6%
Distance: 0.0022% / 0.00002155
4.2
Spanish_Aragon
3.8
Basque_Araba
3.8
Basque_Lower_Navarre
3.4
French_Chalosse
3.2
Basque_Navarre_North
3.2
Spanish_Eivissa
3.0
Basque_Spanish
2.8
Sardinian
2.6
Basque_Navarre_Center
2.4
Spanish_Peri-Barcelona
2.2
Portuguese
2.2
Spanish_Burgos
2.2
Spanish_Pirineu
2.0
Basque_Baztan
2.0
Basque_Gipuzkoa_Southwest
2.0
Spanish_Soria
2.0
Spanish_Terres_de_l'Ebre
1.8
Spanish_Girona
1.6
French_Bearn
1.4
French_Occitanie
1.4
Spanish_Extremadura
1.2
Basque_French
1.2
Basque_Roncal
1.2
Spanish_Lleida
1.0
BelgianC
1.0
Italian_Aosta_Valley
1.0
Spanish_Alacant
1.0
Spanish_Castilla_La_Mancha
1.0
Spanish_Navarra
0.8
Basque_Biscay
0.8
Basque_Soule
0.8
BelgianB
0.8
French_Bigorre
0.8
French_Brittany
0.8
Irish
0.8
Italian_Emilia
0.8
Italian_Umbria
0.8
Saharawi
0.8
Spanish_Aragon_North
0.8
Spanish_La_Rioja
0.8
Spanish_Mallorca
0.8
Spanish_Pais_Vasco
0.8
Spanish_Valencia
0.6
Danish
0.6
French_Corsica
0.6
French_Paris
0.6
Italian_Campania
0.6
Italian_Veneto
0.6
Moroccan_North
0.6
Pomak_Almopia_Plain
0.6
Spanish_Baleares
0.6
Spanish_Camp_de_Tarragona
0.6
Spanish_Castilla_Y_Leon
0.6
Spanish_Catalunya_Central
0.6
Tunisian_Berber_Tamezret
0.4
Abkhasian_Gudauta
0.4
Berber_Tunisia_Chen
0.4
Dutch
0.4
English_Cornwall
0.4
French_South
0.4
German_Hamburg
0.4
Greek_Central_Macedonia
0.4
Greek_Crete_Lasithi
0.4
Greek_Laconia
0.4
Icelandic
0.4
Kurd_Kurmanji_Turkey_o
0.4
Moroccan
0.4
Norwegian
0.4
Roma_Barcelona
0.4
Spanish_Andalucia
0.4
Spanish_Barcelones
0.4
Spanish_Biscay
0.4
Spanish_Canarias
0.4
Spanish_Castello
0.4
Spanish_Galicia
0.4
Swedish
0.4
Swiss_French
0.4
Swiss_Italian
0.4
Tunisian
0.2
Algerian
0.2
Austrian
0.2
Bajo
0.2
Basque_Gipuzkoa
0.2
Belmonte_Jew
0.2
Berber_Algeria
0.2
Berber_MAR_ERR
0.2
Berber_MAR_TIZ
0.2
Bolivian_Cochabamba
0.2
Bolivian_LaPaz
0.2
Cameroon_Mbo
0.2
Colla
0.2
English
0.2
Ethiopian_Mursi
0.2
French_Seine-Maritime
0.2
Fulani_Guinea
0.2
Georgian_Kart
0.2
German_East
0.2
Greek_Arcadia
0.2
Greek_Cyclades_Amorgos
0.2
Greek_Macedonia
0.2
Greek_Peloponnese
0.2
Hungarian
0.2
Igbo
0.2
Indonesian_Bali
0.2
Italian_Calabria
0.2
Italian_Lombardy
0.2
Italian_Molise
0.2
Italian_Northeast
0.2
Italian_Piedmont
0.2
Italian_Tuscany
0.2
Kurdish_Jew
0.2
Mayan
0.2
Mixtec
0.2
Moroccan_Jew
0.2
Mozabite
0.2
Mumbai_Jew
0.2
Nenets_Forest
0.2
Sandawe
0.2
SaudiB
0.2
Senegal_Bedik
0.2
Senegal_Halpularen
0.2
Sicilian_East
0.2
Spanish_Asturias
0.2
Spanish_Cantabria
0.2
Spanish_Murcia
0.2
Swiss_German
0.2
Tunisian_Berber_Matmata
0.2
Tunisian_Berber_Zraoua
0.2
Turkish_North_Macedonia
0.2
Yukpa


Target: Iberian&Amerindian(99+1)94%+SSA6%
Distance: 0.2027% / 0.00202653 | ADC: 0.25x RC
21.2
Spanish_Castilla_La_Mancha
20.2
Spanish_Cantabria
19.8
Spanish_Alacant
19.0
Spanish_Galicia
11.6
Spanish_Murcia
2.8
Portuguese
2.4
Afrikaner
1.8
Madagascar_Mikea
1.2
Chipewyan


Target: Iberian&Amerindian(99+1)94%+SSA6%
Distance: 0.4665% / 0.00466479 | ADC: 0.5x RC
41.6
Spanish_Alacant
34.8
Spanish_Galicia
20.0
Spanish_Murcia
2.0
Tlingit
1.6
Madagascar_Vezo


Target: Iberian&Amerindian(99+1)94%+SSA6%
Distance: 1.2936% / 0.01293592 | ADC: 1x RC
40.4
Spanish_Galicia
34.2
Spanish_Murcia
25.4
Portuguese




Canarian + Berber from Algeria:

Target: Canarian+Berber
Distance: 0.1094% / 0.00109413
37.2
Mozabite
8.6
Saharawi
7.6
Basque_Navarre_Center
7.0
Spanish_Canarias
6.4
Berber_Tunisia_Chen
5.2
Spanish_Peri-Barcelona
4.4
Basque_Navarre_North
4.0
Basque_Soule
3.6
Italian_Friuli_Venezia_Giulia_Sappada
2.4
Moroccan_South
2.4
Tunisia
1.6
Shetlandic
1.6
Spanish_Menorca
1.4
Armenian_Parspatunik
1.2
Spanish_Castilla_Y_Leon
1.0
Spanish_Biscay
1.0
Spanish_Pirineu
0.8
BelgianB
0.8
Yemenite_Al_Jawf
0.6
Berber_MAR_TIZ
0.4
Karaite_Iraq
0.4
Spanish_Camp_de_Tarragona
0.2
French_Brittany
0.2
Fulani


Target: Canarian+Berber
Distance: 0.6221% / 0.00622144 | ADC: 0.25x RC
42.6
Spanish_Canarias
36.2
Moroccan_North
21.2
Algerian


Target: Canarian+Berber
Distance: 0.9927% / 0.00992678 | ADC: 0.5x RC
60.8
Moroccan_North
39.2
Spanish_Canarias


Target: Canarian+Berber
Distance: 2.3986% / 0.02398617 | ADC: 1x RC
68.8
Tunisia
31.2
Spanish_Canarias